Erickson, K. D. | bioRxiv Science

bioRxiv2021

Imprecisely georeferenced specimen data provide unique information on species' distributions and environmental tolerances: Don't let the perfect be the enemy of the good

AimMuseum and herbarium specimen records are frequently used to assess species conservation status and responses to climate change. Typically, occurrences with imprecise geolocality information are discarded because they cannot be matched confidently to environmental conditions, and are thus expected to increase uncertainty in downstream analyses. However, using only precisely georeferenced records risks undersampling of species environmental and geographic distributions. We present two related methods to allow the use of imprecisely georeferenced occurrences in biogeographic analysis. InnovationOur two procedures assign imprecise records to the 1) locations or 2) climates that are closest to the geographic or environmental centroid of the precise records of a species. For virtual species, including imprecise records alongside precise records improved the accuracy of ecological niche models projected to the present and the future, especially for species with ~20 or fewer precise occurrences. Using only precise records underestimates loss in suitable habitat and overestimates the amount of suitable habitat in both the present and future. Including imprecise records also improves estimates of niche breadth and extent of occurrence. An analysis of 44 species of North American Asclepias (Apocynaceae) yielded similar results. Main conclusionsExisting studies examining the effects of spatial imprecision compare outcomes based on precise records to the same records with spatial error added to them. However, in real-world cases, analysts possess a mix of precise and imprecise records and must decide whether to retain or discard the latter. Discarding imprecise records can undersample species geographic and environmental distributions and lead to mis-estimation of responses to past and future climate change. Our method, for which we provide a software implementation in the enmSdmX package for R, is simple to employ and can help leverage the large number of specimen records that are typically deemed "unusable" because of spatial imprecision in their geolocation.

ecology↗

bioRxiv2021

Occupancy-collection models: Towards bias-corrected modeling of species' distributions using unstructured occurrence data from museums and herbaria

The digitization of museum collections as well as an explosion in citizen science initiatives has resulted in a wealth of data that can be useful for understanding the global distribution of biodiversity, provided that the well-documented biases inherent in unstructured opportunistic data are accounted for. While traditionally used to model imperfect detection using structured data from systematic surveys of wildlife, occupancy-detection models provide a framework for modelling the imperfect collection process that results in digital specimen data. In this study, we explore methods for adapting occupancy-detection models for use with biased opportunistic occurrence data from museum specimens and citizen science platforms using 7 species of Anacardiaceae in Florida as a case study. We explored two methods of incorporating information about collection effort to inform our uncertainty around species presence: (1) filtering the data to exclude collectors unlikely to collect the focal species and (2) incorporating collection covariates (collection type and history of previous detections) into a model of collection probability. We found that the best models incorporated both the background data filtration step as well as the incorporation of collector covariates associated with the probability of collection. We found that month, method of collection and whether a collector had previously collected the focal species were important predictors of collection probability. Efforts to standardize meta-data associated with data collection will improve efforts for modeling the spatial distribution of a variety of species.

ecology↗